An Online Framework for Fitting Fast Transient Lightcurves

TL;DR

This paper introduces an online framework for rapidly fitting and identifying fast transient lightcurves, enabling efficient follow-up of potential multi-messenger sources in time-domain astronomy.

Contribution

It presents a new computational pipeline that quickly fits transient lightcurves to various models, improving the speed and accuracy of transient classification.

Findings

Successfully applied to real transient events including a short gamma-ray burst and a supernova.

Demonstrated the pipeline's efficiency in processing and flagging interesting transients for follow-up.

Provided performance metrics and workflow details for the proposed framework.

Abstract

The identification of extragalactic fast optical transients (eFOTs) as potential multi-messenger sources is one of the main challenges in time-domain astronomy. However, recent developments have allowed for probes of rapidly-evolving transients. With the increasing number of alert streams from optical time-domain surveys, the next paradigm is building technologies to rapidly identify the most interesting transients for follow-up. One effort to make this possible is the fitting of objects to a variety of eFOT lightcurve models such as kilonovae and $\gamma$-ray burst (GRB) afterglows. In this work, we describe a new framework designed to efficiently fit transients to light curve models and flag them for further follow-up. We describe the pipeline's workflow and a handful of performance metrics, including the nominal sampling time for each model. We highlight as examples ZTF20abwysqy, the shortest long gamma ray burst discovered to date, and ZTF21abotose, a core-collapse supernova initially identified as a potential kilonova candidate.